Self-regulation of various human behaviors is central to maintaining health and wellbeing. Indeed, failures in self-regulation are implicated in many preventable health problems associated with death and disease, including obesity, poor nutrition, inadequate exercise, and addiction. These problems associated with self- regulation failure also put people at risk for developing various types of cancer, especially in the domains of eating and cigarette smoking. The overarching goal of this research is to determine whether there are reliable neural predictors of real-world behavioral outcomes, specifically the self-regulation of eating and smoking behaviors. In order to accomplish this goal, the studies in this proposal will integrate neuroimaging and experience sampling methods to establish brain-behavior relationships. The proposed studies will involve exposing participants to scenes depicting people eating and smoking (studies 1 and 2, respectively) during a functional MRI (fMRI) scan. Following the fMRI scanning session, participants will be provided with mobile devices for several weeks while they go about their daily routines outside the laboratory environment. These devices will automatically prompt them several times a day to report their momentary thoughts and emotions associated with eating and smoking. The proposed studies will test the specific aims of this project, which include (1) relating reward and motor-related cu reactivity with frequency of real world eating and smoking behaviors, (2) assessing whether individual differences in response inhibition predict regulation of appetitive and addictive behaviors in everyday life, and (3) determining if resting state connectivity between brain regions adds more predictive power for establishing brain-behavior relationships. When taken together, the project's aims serve to elucidate individual differences in self-regulatory capacity n the domains of eating and smoking. Understanding how the basic psychological and neural mechanisms of self-regulatory capacity relate with real world eating and smoking behaviors has many implications for assessing risk factors associated with cancer, addiction, and many other diseases. With a better understanding of these brain-behavior relationships, scientists and clinicians might be better equipped to develop targeted interventions that reduce these risk factors and improve health outcomes.